Cancer survivors are influenced not only by the direct effects of cancer and its treatments but also by common risk factors and sociodemographic characteristics.
Cardio-oncology is a collaborative field between cardiology and oncology aimed at identifying risk factors and preventing cardiovascular disease before, during, and after cancer treatment. Within the initiative Computational Cardio-Oncology, the goal is to use advanced data-driven methods to predict and prevent cardiovascular disease.
Ultimately, the success of Computational Cardio-Oncology will depend on its ability to integrate with traditional clinical approaches and generate insights that can be translated into improved patient care.
To fully realize the potential of this emerging field, a combination of computational and clinical methods will likely be required in the future.
Rebuc-AI
AI-Driven Innovations in Computational Cardio-Oncology: Enhancing Health Registry Research
This project, conducted within the Rebuc study, is a collaboration between the Division of AI and Integrated Computer Systems (AIICS) and the Human-Centered Systems (HCS) division at IDA, together with the Algorithmic Dynamics Lab at Karolinska Institutet.
In this new AI collaboration, we aim to develop a predictive model using the primary database to identify young cancer patients at risk of developing cardiovascular disease.
